• Journal of Korea Multimedia Society
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• v.10 no.3
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• pp.303-315
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• 2007

This paper proposes a 3D structure recovery and registration method that uses four or more common points. For each frame of a given video, a partial structure is recovered using tracked points. The 3D coordinates, camera positions and camera directions are computed at once by our improved scaled orthographic factorization method. The partially recovered point sets are parts of a whole model. A registration of point sets makes the complete shape. The recovered subsets are integrated by transforming each coordinate system of the local point subset into a common basis coordinate system. The process of shape recovery and integration is performed uniformly and linearly without any nonlinear iterative process and without loss of accuracy. The execution time for the integration is significantly reduced relative to the conventional ICP method. Due to the fast recovery and registration framework, our shape recovery scheme is applicable to various interactive video applications. The processing time per frame is under 0.01 seconds in most cases and the integration error is under 0.1mm on average.

• Journal of Korea Multimedia Society
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• v.6 no.2
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• pp.247-258
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• 2003

Principal component analysis (PCA) based algorithms form the basis of numerous algorithms and studies in the face recognition literature. PCA is a statistical technique and its incorporation into a face recognition system requires numerous design decisions. We explicitly take the design decisions by in-troducing a generic modular PCA-algorithm since some of these decision ate not documented in the literature We experiment with different implementations of each module, and evaluate the different im-plementations using the September 1996 FERET evaluation protocol (the do facto standard method for evaluating face recognition algorithms). We experiment with (1) changing the illumination normalization procedure; (2) studying effects on algorithm performance of compressing images using JPEG and wavelet compression algorithms; (3) varying the number of eigenvectors in the representation; and (4) changing the similarity measure in classification process. We perform two experiments. In the first experiment, we report performance results on the standard September 1996 FERET large gallery image sets. The result shows that empirical analysis of preprocessing, feature extraction, and matching performance is extremely important in order to produce optimized performance. In the second experiment, we examine variations in algorithm performance based on 100 randomly generated image sets (galleries) of the same size. The result shows that a reasonable threshold for measuring significant difference in performance for the classifiers is 0.10.

• The Journal of Information Systems
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• v.28 no.3
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• pp.249-276
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• 2019

Purpose The purpose of this study is to develop a prediction model and decision rules for the elderly's suicidal ideation based on the Korean Welfare Panel survey data. By utilizing this data, we obtained many decision rules to predict the elderly's suicide ideation. Design/methodology/approach This study used classification analysis to derive decision rules to predict on the basis of decision tree technique. Weka 3.8 is used as the data mining tool in this study. The decision tree algorithm uses J48, also known as C4.5. In addition, 66.6% of the total data was divided into learning data and verification data. We considered all possible variables based on previous studies in predicting suicidal ideation of the elderly. Finally, 99 variables including the target variable were used. Classification analysis was performed by introducing sampling technique through backward elimination and data balancing. Findings As a result, there were significant differences between the data sets. The selected data sets have different, various decision tree and several rules. Based on the decision tree method, we derived the rules for suicide prevention. The decision tree derives not only the rules for the suicidal ideation of the depressed group, but also the rules for the suicidal ideation of the non-depressed group. In addition, in developing the predictive model, the problem of over-fitting due to the data imbalance phenomenon was directly identified through the application of data balancing. We could conclude that it is necessary to balance the data on the target variables in order to perform the correct classification analysis without over-fitting. In addition, although data balancing is applied, it is shown that performance is not inferior in prediction rate when compared with a biased prediction model.

• Journal of Digital Convergence
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• v.17 no.8
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• pp.197-204
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• 2019

The purpose of this study was to explore factors that influence decision making for smartphone users. This study sets intimacy, personal connection, use & dependence, familiarity and expertise, efficacy and effectance, self-identity, and control as independent variables and sets decision making as dependent variables. In this study, 200 smartphone users were collected and analyzed through questionnaires, and Smartpls 3.0 was used to understand the impact between variables. Five of the six factors that affected smartphone users' psychological strength were analyzed to have affected their decision-making. In addition, we examined the relationship between psychological effects and use period as a control variable. The results of this study can be used as a basis for the consumer behavior of smartphone devices in the development of smartphone devices.

• The Korean Journal of Archival Studies
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• no.70
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• pp.5-40
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• 2021

Administrative information dataset records produced by various systems designed for work are difficult to manage on a case-by-case basis, requiring separate procedures to identify and evaluate data-sets. Identified data set records are apprasal and transferred to the records management system or disposed of. In this process, sufficient records management elements must be reflected in the production system itself in order to adhere to the principles of record management. In this paper, the functional requirements of the production system to accurately identify and safely manage data-sets were derived and applied based on the case of the KR property management system. It is hoped that this research on functional requirements of production systems will be added to lead to the creation of standards for functional requirements of data set production systems.

• Journal of the Korean Geotechnical Society
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• v.36 no.12
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• pp.125-132
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• 2020

Embedded joints in the rock mass are a major constituent influencing its mechanical behavior. Numerical analysis requires a rigorous modeling methodology for the rock mass with detailed information regarding joint properties, orientation, spacing, and persistence. This paper provides a mechanical model for a jointed rock mass based on the implicit joint-continuum approach. Stiffness tensors for rock mass are evaluated for an assemblage of intact rock separated by sets of joint planes. It is a linear summation of compliance of each joint sets and intact rock in the serial stiffness system. In the application example, kinematic analysis for a planar failure of rock slope is comparable with empirical daylight envelope and its lateral limits. Since the developed implicit joint-continuity model is formulated on a continuum basis, it will be a major tool for the numerical simulations adopting published plenteous thermal-hydro-chemical experimental results.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.36 no.4
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• pp.233-242
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• 2023

The unscented Kalman filter (UKF), which is widely used to estimate the states of nonlinear dynamic systems, can be improved to realize robust system identification by using multiple sigma-point sets. When using Kalman filter methods for system identification, artificial noises must be appropriately selected to achieve optimal estimation performance. Additionally, an appropriate scaling factor for the sigma-points must be selected to capture the nonlinearity of the state-space model. This study entailed the use of Bouc-Wen hysteresis model to examine the nonlinear behavior of a single-degree-of-freedom oscillator. On the basis of the effects of the selected artificial noises and scaling factor, a new UKF method using multiple sigma-point sets was devised for improved robustness of the estimation over various signal-to-noise-ratio values. The results demonstrate that the proposed method can accurately track nonlinear system states even when the measurement noise levels are high, while being robust to the selection of artificial noise levels.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1512-1512
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• 2001

The University of Cordoba conducts since 1991 a breeding program to obtain new olive cultivars from intraspecific crosses. The objective is to obtain new early bearing and high-quality cultivars. In plant breeding, many seedlings must be tested to increased the chance of getting desirable genotypes. Therefore, fast, cheap and accurate methods of analysis are necessary. The conventional laboratory techniques are costly and time-consuming. Near Infrared Spectroscopy (NIRS) can satisfy the characteristics requested by plant breeders and offers many advantages such as the simultaneous analysis of many traits and cheap cost. The objective of this work was to asses the performance of NIRS to estimate oil fruit components (fruit weight, flesh moisture, flesh/stone ratio and oil flesh content in dry weight basis) and fatty acid composition in olive fruit. Genotypes from reciprocal crosses between ‘Arbequina’, ‘Frantoio’ and ‘Picual’ cultivars have been used in this study. A total of 287 samples, each from a single plant, were scanned using a DA-7000 Diode Array VIS/NIR Analysis System (Perten Instruments), which covers the visible and NIR range from 400-1700 nm. All samples were analysed for fatty acid composition (gas chromatography) and 220 for oil fruit components (oil content by nuclear magnetic resonance), 70% and 30% of samples were randomly assign for the calibration and validation sets respectively. The preliminary results shows that calibration for palmitic, oleic and linoleic acids were highly accurate with calibration and validation values of $r^2$ from 0.85 to 0.95 and 0.76 to 0.91 respectively. Calibration for palmitoleic and estearic acids were less accurate, probably because of the narrow range of variability available for these fatty acids. For the oil fruit components, calibration were high accurate for flesh moisture and oil flesh content in dry weight basis ($r^2$ higher than 0.90 in both calibration and validation sets) and less accurate for the other characteristics evaluated. The first results obtained indicate that NIRS analysis could be an ideal technique to reduce the cost, time and chemical wasted necessary to evaluate a large number of genotypes and it is accurate enough to use for pre-selecting genotypes in a breeding program.

• Journal of KIISE:Software and Applications
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• v.37 no.6
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• pp.455-463
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• 2010

In this paper, we present an approach to sentence boundary detection for web documents that builds on statistical-based methods and uses rule-based correction. The proposed system uses the classification model learned offline using a training set of human-labeled web documents. The web documents have many word-spacing errors and frequently no punctuation mark that indicates the end of sentence boundary. As sentence boundary candidates, the proposed method considers every Ending Eomis as well as punctuation marks. We optimize engine performance by selecting the best feature, the best training data, and the best classification algorithm. For evaluation, we made two test sets; Set1 consisting of articles and blog documents and Set2 of web community documents. We use F-measure to compare results on a large variety of tasks, Detecting only periods as sentence boundary, our basis engine showed 96.5% in Set1 and 56.7% in Set2. We improved our basis engine by adapting features and the boundary search algorithm. For the final evaluation, we compared our adaptation engine with our basis engine in Set2. As a result, the adaptation engine obtained improvements over the basis engine by 39.6%. We proved the effectiveness of the proposed method in sentence boundary detection.

• Journal of Korean Society for Atmospheric Environment
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• v.17 no.2
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• pp.119-131
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• 2001

A total of 328 ambient PM-10 samples was collected by a PM-10 high volume air sampler during the periods of February 1997 to February 1999 from Kyung Hee University at Suwon Campus. The samples were analyzed for their bulk chemical compositions(Cu, Fe, Pb, Zn, Al, $Na^{+}$, $NH_{4}^{+}$, $K^{+}$, $Ca^{2+]$, $Mg^{2+}$, $Cl^{-}$, $NO_{3}^{-}$, and $SO_{4}^{2-}$ by both an atomic absorption spectrophotometer and an ion chromatograph. The purpose of this study was t develop a receptor methodology for quantitative assessment of PM-10 sources. The data obtained from this study were ex-tensively examined using the target transformation factor analysis(TTFA) and the chemical mass balance (CMB). When TTFA was initially applied seasonal basis. five sources(such as automobile-related, sulfate-related, incine-ration, soil and combustion-related) were identified both during winter and fall. Since the total number and the type of sources were resolved by TTFA for the four seasons, CMB was employed to cross-check the results of TTEA. The total of six source categories identified by TTEA was intensively investigated on the basis of source profiles acquired from various source libraries established both in Korea and abroad. The results of this study showed the applicability of two popular receptor models as a new methdology for quantitative assessment PM-10 sources in Korea. Seasonally segmented data sets with the combined application of TTFA and CMB yielded a physically reasonable source apportionment result and provided a mean to increase the number of potential sources. Furthermore, this study suggested the possibility of the CMB application to ambi-ent data from Korea after identifying potential sources through traditional factor analysis.